A common test of pneumatic tires is to run a test tire under controlled test conditions including (rotational) speed, loading (force between the tire and the running surface), tire fill pressure, and ambient conditions. Typically the state of the tire is measured both continuously while running, and periodically when stopped for various static tests such as x-rays, visual checks, temperature profile, and the like. The continuous measurements include tire pressure, average temperature, and importantly, tire vibration as detected by one or more vibration sensors (typically force transducers and/or accelerometers).
Tire vibration measurements are typically performed on production tires as a quality check of the “tire uniformity”. A tire with excellent uniformity will produce very low vibration amplitudes when rotated at high speed with or without a load. In contrast, an out of balance tire will produce an abnormally high first harmonic amplitude, i.e., a peak that repeats once per rotation of the tire. This can also be described as producing a vibration signal that is periodic with a frequency equal to the rotational speed of the tire. The vibration signal is a plot of vibration amplitude versus running time of the tire. The term “vibration” is used herein as a generic term for displacement, force, or acceleration, depending upon which characteristic is being sensed and/or calculated from the “vibration” sensor output data. In other words, the “vibration signal” is essentially a plot of sensor output versus time, where the sensor is typically either a force transducer or an accelerometer that is suitably mounted on the tire testing machine.
A vibration signal (vibration amplitudes plotted in the time domain) can be converted to a frequency domain plot (spectrum) through the use of Fourier transforms, particularly the quick approximation resulting from a computer algorithm known as a fast Fourier transform (FFT). The FFT spectrum shows the relative amount of vibration at each frequency from a low limit to a high frequency limit, where the limits are determined by sensor capability and by knowledge of the range of frequencies that produce useful information. For example, a typical automobile tire on a vehicle traveling at 100 miles per hour (161 kilometers per hour) will rotate about 25 times per second, i.e., 25 Hz (Hertz, cycles per second). In this example, the first harmonic is therefore 25 Hz; the second harmonic is two times that or 50 Hz; the third harmonic is three times that or 75 Hz; and so on. Thus an FFT spectrum (harmonic spectrum) calculated out to 500 Hz is sufficient to show vibration magnitudes out to the 20th harmonic for this example. Since tire test equipment generally uses a rotational angle detector (encoder), the rotational speed (angular velocity) of the tire is always known, and therefore the harmonic spectrum's frequency axis can be normalized to a harmonic scale (integer values of the harmonics).
Analysis of the harmonic spectrum for a tire test can indicate many different tire conditions. For example, as stated above, the first harmonic magnitude increases with the amount of tire imbalance. In another example, since a tire “footprint” is generally about one sixth of a tire's circumference, a “flat spot” the size of the footprint will produce an unusually high magnitude sixth harmonic when the tire is running under load. It has long been known that magnitudes of typically the first five harmonics and sometimes even the sixth or seventh harmonics, are more indicative of gross effects that are humanly discernable as characteristics of the “ride”. Gross effects are typically tire non-uniformities that occur over a relatively large area of the tire, such as mass non-uniformities that cause static or dynamic imbalance, and such as tire shape non-uniformities like out-of-roundness, conicity, tread squirm, uneven tread wear, etc.
In 1985, the inventor reported on “Fourier Transform Applications to Tire Life Testing” (published: Tire Science and Technology; Vol. 15, No. 3, July-September, 1987, pp. 173-187). For the purpose of tire life testing, the “end of life” for a tire (not counting tread wear) is when the tire undergoes catastrophic failure such as a blow-out or a major separation of tire components (often loss of tread pieces). In his paper, the inventor reported observing that higher harmonics undergo significant magnitude changes (both increases and decreases) before and during catastrophic failure of the tire. Furthermore, higher harmonic magnitude changes occur quite rapidly near to the time of tire failure. He noted that this makes sense since higher harmonics are important for detecting very localized changes in tire structure. The term “higher harmonics” generally means harmonic 6 and above. Thus monitoring magnitudes of the higher harmonics during a tire test is useful for detecting warning indications of immanent catastrophic failure. Given a warning, the life test can be immediately halted so that the tire can be analyzed in detail for determination of the cause of failure. If the tire had been allowed to fail catastrophically, then such detailed analysis would be much more difficult and would yield far less detailed results.
In the case of vehicles riding on pneumatic tires (e.g., automobiles, motorcycles and trucks) catastrophic failure is at the very least upsetting and inconvenient, and can even be the cause of lethal accidents. Therefore immanent failure warning for vehicular tires is very desirable. Compared to tire testing machines, vehicles present a number of significant challenges to the simple application of the harmonic spectrum monitoring method presented above. One of the major challenges is that a vehicle always has a plurality of tires (at least two) that are concurrently operating at roughly the same rotational speed determined by the vehicle speed and the fact that all the tires are usually the same diameter. Since all the tires are connected quite solidly to the same vehicle frame, the vibrations measured by a sensor at one tire will necessarily include vibration generated by all of the other tires connected to the same frame. Another challenge is the extraneous vibrations (“noise”) generated by drive shafts, bearings, CV joints, U joints, differentials, the engine, and the like, all of which generate cyclic (periodic) vibration signals which will be picked up by the vibration sensors mounted at the wheels. Finally, there will also be non-cyclic (random) vibrations such as wind noise and especially road noise (due to the road surface upon which the tires are running).
There are numerous publications in the prior art that disclose various techniques for eliminating machine noise or machine contributions to the tire vibration signal measured on tire test machines. For example, U.S. Pat. No. 6,655,202 (Potts et al.; 2003) discloses the use of a plurality of accelerometers that allow the forces and the moments of the components of the measurement station to be calculated and accounted for in the overall force measurement. For example, U.S. Pat. No. 6,705,156 (Shteinhauz et al.; 2004) discloses a cross-correlation method for identification and removal of machine contribution from tire uniformity measurements. Cross correlation is a well known mathematical technique for comparing multiple periodic signals to determine a time/angle shift that will optimally synchronize one signal with another so that the multiple signals can be combined and averaged to eliminate (average out) noise components in the signals.
It is an object of the present invention to advance the state of the art such that immanent tire failure warning techniques developed on individual tire test machines can be applied to situations wherein a plurality of tires are concurrently operating and interacting with each other through a common structure. A primary objective is to develop such a warning system and method for automotive vehicles, but other applications are also anticipated, as will be described hereinbelow.